In recent years, geography has acquired a great importance in the context of Information Retrieval (IR) and, in general, of the automated processing of information in text. Mobile devices that are able to surf the web and at the same time inform about their position are now a common reality, together with applications that can exploit these data to provide users with locally customised information, such as directions or advertisements. Therefore, it is important to deal properly with the geographic information that is included in electronic texts. The majority of such kind of information is contained as place names, or toponyms.

Toponym ambiguity represents an important issue in Geographical Information Retrieval (GIR), due to the fact that queries are geographically constrained. There has been a struggle to find specific geographical IR methods that actually outperform traditional IR techniques. Toponym ambiguity may constitute a relevant factor in the inability of current GIR systems to take advantage from geographical knowledge. Recently, some Ph.D. theses have dealt with Toponym Disambiguation (TD) from different perspectives, from the development of resources for the evaluation of Toponym Disambiguation to the use of TD to improve geographical scope resolution. The Ph.D. thesis presented here introduces a TD method based on WordNet and carries out a detailed study of the relationship of Toponym Disambiguation to some IR applications, such as GIR, Question Answering (QA) and Web retrieval.

The work presented in this thesis starts with an introduction to the applications in which TD may result useful, together with an analysis of the ambiguity of toponyms in news collections. It could not be possible to study the ambiguity of toponyms without studying the resources that are used as placename repositories; these resources are the equivalent to language dictionaries, which provide the different meanings of a given word. An important finding of this Ph.D. thesis is that the choice of a particular toponym repository is key and should be carried out depending on the task and the kind of application that it is going to be developed. We discovered, while attempting to adapt TD methods to work on a corpus of local Italian news, that a factor that is particularly important in this choice is represented by the ``locality" of the text collection to be processed. The choice of a proper Toponym Disambiguation method is also key, since the set of features available to discriminate place references may change according to the granularity of the resource used or the available information for each toponym. In this work we developed two methods, a knowledge-based method and a map-based method, which compared over the same test set.

We studied the effects of the choice of a particular toponym resource and method in GIR, showing that TD may result useful if query length is short and a detailed resource is used. We carried out some experiments on the CLEF GIR collection, finding that retrieval accuracy is not affected significantly, even when the errors represent 60\% of the toponyms in the collection, at least in the case in which the resource used has a little coverage and detail. Ranking methods that sort the results on the basis of geographical criteria were observed to be more sensitive to the use of TD or not, especially in the case of a detailed resource. We observed also that the disambiguation of toponyms does not represent an issue in the case of Question Answering, because errors in TD are usually less important than other kind of errors in QA.

In GIR, the geographical constraints contained in most queries are area constraints, such that the information need usually expressed by users can be resumed as ``X in P", where P is a place name, and X represents the thematic part of the query. A common issue in GIR occurs when a place named by a user cannot be found in any resource because it is a fuzzy region or a vernacular name. In order to overcome this issue, we developed Geooreka!, a prototype search engine with a map-based interface. A preliminary testing of this system is presented in this work. The work carried out on this search engine showed that Toponym Disambiguation can be particularly useful on web documents, especially for applications like Geooreka! that need to estimate the occurrence probabilities for places.